linear velocity transducer, 2 linear position transducers, 1 camera-based optoelectronic device, 2 inertial measurement units, and 1 smartphone application) to predict the 1RM from the individual load–velocity relationship modeled by 5 (multiple-point method) or 2 (2-point method) loads during the
Alejandro Pérez-Castilla, Antonio Piepoli, Gabriel Garrido-Blanca, Gabriel Delgado-García, Carlos Balsalobre-Fernández and Amador García-Ramos
Loren Z.F. Chiu, Brian K. Schilling, Andrew C. Fry and Lawrence W. Weiss
Displacement-based measurement systems are becoming increasingly popular for assessment of force expression variables during resistance exercise. Typically a linear position transducer (LPT) is attached to the barbell to measure displacement and a double differentiation technique is used to determine acceleration. Force is calculated as the product of mass and acceleration. Despite the apparent utility of these devices, validity data are scarce. To determine whether LPT can accurately estimate vertical ground reaction forces, two men and four women with moderate to extensive resistance training experience performed concentric-only (CJS) and rebound (RJS) jump squats, two sessions of each type in random order. CJS or RJS were performed with 30%, 50%, and 70% one-repetition maximum parallel back squat 5 minutes following a warm-up and again after a 10-min rest. Displacement was measured via LPT and acceleration was calculated using the finite-difference technique. Force was estimated from the weight of the lifter-barbell system and propulsion force from the lifter-barbell system. Vertical ground reaction force was directly measured with a single-component force platform. Two-way random average-measure intraclass correlations (ICC) were used to assess the reliability of obtained measures and compare the measurements obtained via each method. High reliability (ICC > 0.70) was found for all CJS variables across the load-spectrum. RJS variables also had high ICC except for time parameters for early force production. All variables were significantly (p < 0.01) related between LPT and force platform methods with no indication of systematic bias. The LPT appears to be a valid method of assessing force under these experimental conditions.
Jennifer J. Sherwood, Cathy Inouye, Shannon L. Webb and Jenny O
studies using an LPT to measure power, findings from Herman et al. ( 2005 ) suggest that some mechanisms affecting power are unique, and additional research beyond the context of the current study is needed. Linear position transducer technology has well established relevance for velocity-based training
Irineu Loturco, Lucas A. Pereira, Ciro Winckler, Weverton L. Santos, Ronaldo Kobal and Michael McGuigan
-training intensity by the instantaneous measurement of the movement velocity. 1 , 3 Although a recent study 4 revealed possible disparities among different methods for determining mechanical outputs in strength–power exercises, the variety of technologies available (eg, accelerometer, linear position transducer
Jacob A. Goldsmith, Cameron Trepeck, Jessica L. Halle, Kristin M. Mendez, Alex Klemp, Daniel M. Cooke, Michael H. Haischer, Ryan K. Byrnes, Robert F. Zoeller, Michael Whitehurst and Michael C. Zourdos
attaching LPTs to barbell; 7 = reference line for squat walkout to achieve perpendicular angle of LPT cords; 8 = barbell on squat rack; and 9 = connecting cables from OC3D to computer and from computer to OC3D sensors. LPT indicates linear position transducer; OC3D, Optotrak Certus 3-dimensional motion
Amador García-Ramos, Alejandro Torrejón, Belén Feriche, Antonio J. Morales-Artacho, Alejandro Pérez-Castilla, Paulino Padial and Guy Gregory Haff
Purpose: To provide 2 general equations to estimate the maximum possible number of repetitions (XRM) from the mean velocity (MV) of the barbell and the MV associated with a given number of repetitions in reserve, as well as to determine the between-sessions reliability of the MV associated with each XRM. Methods: After determination of the bench-press 1-repetition maximum (1RM; 1.15 ± 0.21 kg/kg body mass), 21 men (age 23.0 ± 2.7 y, body mass 72.7 ± 8.3 kg, body height 1.77 ± 0.07 m) completed 4 sets of as many repetitions as possible against relative loads of 60%1RM, 70%1RM, 80%1RM, and 90%1RM over 2 separate sessions. The different loads were tested in a randomized order with 10 min of rest between them. All repetitions were performed at the maximum intended velocity. Results: Both the general equation to predict the XRM from the fastest MV of the set (CV = 15.8–18.5%) and the general equation to predict MV associated with a given number of repetitions in reserve (CV = 14.6–28.8%) failed to provide data with acceptable between-subjects variability. However, a strong relationship (median r 2 = .984) and acceptable reliability (CV < 10% and ICC > .85) were observed between the fastest MV of the set and the XRM when considering individual data. Conclusions: These results indicate that generalized group equations are not acceptable methods for estimating the XRM–MV relationship or the number of repetitions in reserve. When attempting to estimate the XRM–MV relationship, one must use individualized relationships to objectively estimate the exact number of repetitions that can be performed in a training set.
Alejandro Pérez-Castilla, Daniel Jerez-Mayorga, Dario Martínez-García, Ángela Rodríguez-Perea, Luis J. Chirosa-Ríos and Amador García-Ramos
Purpose: To compare the load–velocity (L-V) relationship between bench-press exercises performed using 4 different grip widths, to determine the association between the anthropometric characteristics and L-V profile, and to explore whether a multiple linear-regression model with movement velocity and subjects’ anthropometric characteristics as predictor variables could increase the goodness of fit of the individualized L-V relationship. Methods: The individual L-V relationship of 20 men was evaluated by means of an incremental loading test during the bench-press exercise performed on a Smith machine using narrow, medium, wide, and self-selected grip widths. Simple and multiple linear-regression models were performed. Results: The mean velocity associated with each relative load did not differ among the 4 grip widths (P ≥ .130). Only body height and total arm length were correlated with the mean velocity associated with light and medium loads (r ≥ .464). A slightly higher variance of the velocity attained at each relative load was explained when some anthropometric characteristics were used as predictor variables along with the movement velocity (r 2 = .969 [.965–.973]) in comparison with the movement velocity alone (r 2 = .966 [.955–.968]). However, the amount of variance explained by the individual L-V relationships was always higher than with the multiple linear-regression models (r 2 = .995 [.985–1.000]). Conclusions: These results indicate that the individual determination of the L-V relationship using a self-selected grip width could be recommended to monitor relative loads in the Smith machine bench-press exercise.
Justin J. Merrigan, James J. Tufano, Jonathan M. Oliver, Jason B. White, Jennifer B. Fields and Margaret T. Jones
Technology Inc (AMTI), Watertown, MA) with 4 linear position transducers (PT5A-150 Celesco; Measurement Specialties Inc, Chatsworth, CA) attached to the bar on the inside of both collars. The cables were mounted above and anterior and above and posterior, to the subject, to form 2 triangles when attached to
Prue Cormie, Jeffrey M. McBride and Grant O. McCaulley
The objective of this study was to investigate the validity of power measurement techniques utilizing various kinematic and kinetic devices during the jump squat (JS), squat (S) and power clean (PC). Ten Division I male athletes were assessed for power output across various intensities: 0, 12, 27, 42, 56, 71, and 85% of one repetition maximum strength (1RM) in the JS and S and 30, 40, 50, 60, 70, 80, and 90% of 1RM in the PC. During the execution of each lift, six different data collection systems were utilized; (1) one linear position transducer (1-LPT); (2) one linear position transducer with the system mass representing the force (1-LPT+MASS); (3) two linear position transducers (2-LPT); (4) the force plate (FP); (5) one linear position transducer and a force plate (1-LPT+FP); (6) two linear position transducers and a force place (2-LPT+FP). Kinetic and kinematic variables calculated using the six methodologies were compared. Vertical power, force, and velocity differed significantly between 2-LPT+FP and 1-LPT, 1-LPT+MASS, 2-LPT, and FP methodologies across various intensities throughout the JS, S, and PC. These differences affected the load–power relationship and resulted in the transfer of the optimal load to a number of different intensities. This examination clearly indicates that data collection and analysis procedures influence the power output calculated as well as the load–power relationship of dynamic lower body movements.
Dustin J. Oranchuk, Eric J. Drinkwater, Riki S. Lindsay, Eric R. Helms, Eric T. Harbour and Adam G. Storey
the laboratory and completed the same testing protocol from the previous week, with the opposite grip. Data Collection and Analysis Kinetic and kinematic data were collected via a dual linear position transducer (LPT; Fittech, Adelaide, Australia) system sampling at 500 Hz. 19 The LPT system was